Virtual prototyping and testing for medical device development

ABSTRACT

A system and method of developing better-designed medical devices, particularly cardiovascular stents and endovascular grafts. The system comprises a geometry generator, a mesh generator, a stress/strain/deformation analyzer, and a visualization tool. In one embodiment, the geometry generator receives three-dimensional volumetric data of an anatomical feature and generates a geometric model. The mesh generator then receives such geometric model of an anatomical feature or an in vitro model and a geometric model of a candidate medical device. In another embodiment, the mesh generator only receives a geometric model of the candidate medical device. Using the geometric model(s) received, the mesh generator creates or generates a mesh or a finite element model. The stress/strain/deformation analyzer then receives the mesh, and the material models and loads of that mesh. Using analysis, preferably non-linear analysis, the stress/strain/deformation analyzer determines the predicted stresses, strains, and deformations on the candidate medical device. Such stresses, strains, and deformations may optionally be simulated visually using a visualization tool.

RELATED PATENT APPLICATION

This patent application is a continuation and claims the benefit of U.S.patent application Ser. No. 09/679,725, filed Oct. 4, 2000 now U.S. Pat.No. 7,840,393, naming Robert G. Whirley and Michael V. Chobotov asinventors, entitled VIRTUAL PROTOTYPING AND TESTING FOR MEDICAL DEVICEDEVELOPMENT, the entirety of which is incorporated by reference herein,including all text and drawings.

BACKGROUND

1. Field of the Invention

This invention relates to systems and methods of developingbetter-designed medical devices, specifically, intracorporeal medicaldevices and particularly cardiovascular stents and endovascular grafts.

2. Background and Description of Related Art

Atherosclerotic vascular disease is a significant health problem facingthe world population today. Atherosclerosis results in two primary typesof lesions—occlusive and aneurysmal, with the aorta being the primarysite of aneurysmal disease. Occlusive disease is a process in which avessel lumen becomes narrowed and the blood flow restricted. Occlusivedisease is typically associated with plaque buildup on the vessel wallor a biological response to vessel injury. One approach to treatment ofocclusive disease involves placing a stent inside the vessel to act as astructural scaffold and hold open the vessel, and also possibly toprovide local drug delivery or local radiation treatment. Aneurysmaldisease is a process in which a vessel dilates under the influence ofhemodynamic pressure, and may ultimately lead to rupture of the vesseland severe internal bleeding. One approach to treatment of aneurysmaldisease involves placing a TPEG (transluminally placed endovasculargraft, or “stent graft”) across the aneurysm, excluding the aneurysmfrom hemodynamic pressure and thereby reducing or eliminating the riskof rupture. Examples of such grafts can be found in co-pending U.S.patent application Ser. No. 09/133,978, filed Aug. 14, 1998 by Chobotov,which is hereby incorporated by reference herein in its entirety.

A TPEG is an endovascular prosthetic device that lines the interior ofan artery to provide flow path integrity and structural support to thedamaged or diseased blood vessel. TPEGs are sometimes called “stentgrafts” because they were originally created using combinations ofstents and synthetic vascular graft segments. TPEGs are delivered to ablood vessel location in a compressed state, through an incision, andare then deployed at the location of concern.

The current development process of TPEGs and medical devices generally,usually involves the reiterative and sequential steps of designing,fabricating the prototype, and testing the prototype until the requiredperformance specifications are met. Fabrication of the prototype entailsthe building of the actual medical device, e.g., a TPEG. Testing caninvolve animal testings, human clinical trials, stress, strain, anddeformation testing, and the like. Stents, TPEGs and other medicaldevices have suffered from long development times and from designdeficiencies discovered late in the development and testing process.Thus, the development of improved medical devices could be significantlyaccelerated if design deficiencies could be identified earlier, beforecommitting to lengthy laboratory testing, animal studies, and humanclinical trials. A system that enables early evaluation of many aspectsof device performance in vivo, and is applicable to development ofstents for occlusive disease, TPEGs for aneurysmal disease, and othermedical devices is highly desirable.

In designing a TPEG, several factors must be taken into account, such asthe structural integrity of the TPEG, the prevention of perigraft leaks,the need for a more easily-controlled TPEG deployment to allow a moreprecise positioning of the TPEG, the kink resistance of the TPEG, themorphology of the arterial walls, the relatively large size and lack ofTPEG flexibility in the undeployed configuration (which can createdifficulties in passing the TPEG from its insertion site to itsdeployment site), and the like. In vivo boundary conditions and forces,particularly dynamic or static cyclic in vivo forces, and the materialproperties of a TPEG are also important factors. Taking these factorsinto consideration during virtual testing and development of a medicaldevice generates a more accurate assessment of the maximum stresses,strains, and deformations, over time that may potentially be handled bya medical device such as a TPEG.

In designing a stent, several factors must be considered includingradial force, crush resistance, flexibility (in both the compressed andthe deployed configurations), fatigue life, and tissue intrusion throughopen stent cells. A system that allows rapid evaluation of these andother characteristics of a stent design before hardware prototypes areconstructed, thereby reducing the cost and time required for developmentand also expanding the designer's capability to explore more exoticdesigns and possibly discover new and more advantageous stent designswithin a given budget and timeframe is highly desirable.

Thus, systems and methods which allow accurate virtual testing of amedical device design with respect to one or more of the above notedfactors, in addition to other factors not specifically enumerated,without the need for an actual prototype of the design, are needed. Suchsystems and methods can reduce the cost of medical device developmentand increase the safety and efficacy of the designs.

SUMMARY

The invention provides a system and method for developingbetter-designed medical devices and particularly cardiovascular stentsand endovascular grafts. The system comprises a Geometry Generator, aMesh Generator, a Stress/Strain/Deformation Analyzer, and, optionally, aVisualization tool. The invention may obtain anatomic data from 3Dvolumetric data. In other embodiments, the invention utilizes anidealized anatomical feature, an in vitro model, or no anatomicalfeature at all.

In one embodiment, the Geometry Generator receives three-dimensionalvolumetric data of an anatomical feature and accordingly extracts thesurface points of such data, which in turn is received by the MeshGenerator. In another embodiment, the Geometry Generator based onalgorithms available in such Geometry Generator software generates anoutput that is directly received by the Mesh Generator. Using the outputgenerated by the Geometry generator and the geometric model of acandidate medical device, the Mesh Generator generates a mesh or afinite element model incorporating either the anatomical feature or invitro model and candidate medical device. In an embodiment where noanatomical feature is used, a mesh only incorporating the candidatemedical device is generated. The Stress/Strain/Deformation Analyzer thenreceives the mesh and the material models, the loads and/ordisplacements placed on the anatomical feature or in vitro model, ifapplicable, and the candidate medical device. Using stress and straindeformation analysis, particularly non-linear analysis, theStress/Strain/Deformation Analyzer simulates and analyzes the potentialin vivo stresses, strains, and deformations or motions of the candidatemedical device. Such strains, stresses, and deformations may optionallybe displayed using a Visualization tool.

Various embodiments of the invention can be used to provide a variety ofuseful functions and capabilities to those who design, manufacture anduse medical devices. Specifically, embodiments of the invention may beused to model anatomical features or anatomical environmentsdynamically. As a result, a computer generated model of a medicaldevice, or the like, may be virtually placed or deployed within theanatomical model to measure the response of the device to theenvironment. The dynamics of the computer generated model of theanatomical features or environment can be accelerated dramatically suchthat large numbers of normal biological cycle, such as a heartbeat, canbe imposed upon the computer generated medical device model in arelatively short period of time.

This gives medical device designers the ability to virtually test aproposed design in a short period of time relative to the time it wouldtake for a similar number of dynamic biological cycles in vivo. Thus,the iterative process of device design and testing of designs isaccelerated and improvements in medical device technology can beachieved at a quicker rate. Further, embodiments of the invention can beused to vary and test material properties of medical device componentsover a broad range in a short period of time using the non-linearmodeling capabilities of the embodiments. This capability can be used toselect materials having optimal properties for producing the safest andmost efficacious designs within a given set of design parameters.

Another benefit of embodiments of the invention is directed to varyingmaterial and configuration properties of models of anatomical featuressuch that a simulation of testing of a given device could be performedin a large number of patients, as might be carried out in a large scaleclinical trial. If the statistical variation of tissue parameters of agiven anatomical feature is known for a given patient population, amedical device model could be tested in anatomical models which varyover such a given range. In this way, a large scale clinical trial couldbe modeled with embodiments of the invention, at least as to certainperformance parameters, without the need for large numbers of actualpatients being subjected to clinical testing. The data generated fromsuch a clinical trial modeling exercise could be used to produce orrefine the design of a medical device such that it performs optimallyover a broad range of anatomical environments. The design could berefined using such data to improve robustness and adaptability of themedical device design.

Also, it is possible to use embodiments of the invention to identifyfailure modes of given medical device designs when such designs aresubjected to dynamic mechanical and chemical forces. By identifying thecause of failure in a design, the “weak link” in the design can bepinpointed and necessary corrections to materials or configuration madein order to obviate the problem. It is also possible to test theories offailure experienced during in vivo clinical testing using embodiments ofthe invention. In other words, if an in vivo clinical failure of amedical device should occur, there may be one or more theoriespostulated as to the cause of the failure, particularly in a situationwhere multiple components of a device have failed and it is not clearfrom the clinical data which failure occurred first, or if an initialfailure of one component of the device precipitated subsequent failureof other components of the device. The dynamic modeling capabilities ofembodiments of the invention can allow rapid testing of multipletheories as to the timing and causation of complex failure modes andquickly determine which of the postulated theories is correct.

In addition, the dynamic, non-linear analysis modeling capabilities ofembodiments of the invention allow a physician, who is responsible foruse or implementation of a medical device, to more accurately choose aproper size or type of medical device based on a specific patient'sanatomy. Such is the case when a specific patient's anatomy oranatomical feature is substantially duplicated by a computer model of anembodiment of the invention generated from 3-D volumetric image data, orthe like. A large number of sizes or types of virtual medical devicescan then be placed and tested within the patient's specific anatomicalfeature to determine optimum safety and efficacy of the design choice.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram representation of a virtualprototyping system having features of the present invention.

FIG. 2 illustrates a block diagram showing data received by anembodiment of a Geometry Generator and a Mesh Generator in accordancewith the present invention.

FIG. 3 illustrates a block diagram representation of another embodimentof a system of the present invention.

FIG. 4 illustrates a block diagram showing data received by aStress/Strain/Deformation Analyzer.

FIGS. 5A-5M contain an exemplary text of a command file that is read bya Mesh Generator, such as TRUEGRID, to conduct a component-levelanalysis of a stent, without the option for simulating deployment intoCT-based anatomy.

FIGS. 6A-6F contain an exemplary text of a command file read by TRUEGRIDfor a simulated TPEG graft deployment in a proximal aortic neck togenerate a mesh incorporating both an anatomical feature and medicaldevice and to output files that are read by a Stress/Strain/DeformationAnalyzer.

FIGS. 7A-7C contain an exemplary include file used by the command filelisted in FIGS. 6A-6F.

FIGS. 8A-8L contain another exemplary command file read by TRUEGRID usedin the virtual prototyping system of the present invention forsimulating stent deployment into an anatomy from CT data, as opposed toa stent graft deployment.

FIGS. 9A and 9B illustrate a process to develop better-designed medicaldevices, particularly TPEGs, in accordance with an embodiment of thepresent invention using 3D volumetric data.

FIG. 10 illustrates a process to develop better-designed medical devicesusing in vitro anatomical features.

FIG. 11 illustrates the use of an embodiment of the present invention asa physician preprocedure planning tool.

FIG. 12 contains a representation of one simulation display of a cutawaylateral view of a vascular stent in the infrarenal aorta just proximalto an abdominal aneurysm.

FIG. 13 is a block diagram representation of one of the computersillustrated in FIG. 1.

DETAILED DESCRIPTION

The following detailed description illustrates an embodiment of theinvention by way of example, not by way of limitation of the principlesof the invention. Various embodiments of the invention will be describedby way of illustration with reference to various software tools, but itshould be understood that other software tools that have a comparablecapabilities of the mentioned tools may be used and other medical deviceaside from TPEGs may also be developed using this invention. Inaddition, although the invention is discussed in the context ofprosthesis and specifically endovascular grafts, this is in no way meantto limit the scope of the invention.

Systems and methods of embodiments of the invention are suitable for thedevelopment and testing of medical devices including those fortherapeutic, diagnostic, monitoring and the like purposes. In general,any device that interacts inside a patient's body may be betterdeveloped and tested with the systems and methods of embodiments of thepresent invention.

Embodiments of the present invention are also well suited fordevelopment and testing of intracorporeal devices or prosthesis thatgenerally have an acute interaction with anatomical features of apatent. A list of such devices, which is in no way exhaustive, couldinclude endovascular grafts, stents, pacemakers, artificial joints,artificial tendons, heart valves, artificial limbs, orthopedic hardware,surgical equipment such as sutures, staples, etc., and the like.

Embodiments of the present inventions are particularly well suited forthe development and testing of devices for use in the vascular system orother bodily systems that have stresses, strains, and deformations whichare dynamic, or quasi-static, and cyclic in nature, e.g., the rhythmicpulsing of the arterial system resulting from variations in bloodpressure from the patent's beating heart and the resulting cyclicdynamic or quasi-static stresses, strains, and deformations thesevariations impart on the patient's arteries and medical devices disposedtherein or thereon.

Embodiments of the present invention are also suitable for developmentand testing of interventional medical devices, which have only transientor temporary contact with the anatomical features of a patient.Illustrative examples of such devices can include catheters, balloons,atherectomy devices, guidewires, and the like.

FIG. 1 is a block diagram showing one embodiment of a virtualprototyping system 105 for analyzing the use of a medical deviceconstructed in accordance with an embodiment of the present invention.FIG. 1 shows that a Geometry Generator 120 receives CT scan or MRI Data110 as input. The Geometry Generator 120 then processes the CT scan orMRI data and outputs data, which are then received by the Mesh Generator130 as input. The Mesh Generator, in addition to receiving the output ofthe Geometry Generator 120, also receives a Medical Device Model data140 as input. The Medical Device Model 140 contains the geometry(geometric shape or geometric model) of the candidate medical device.Such model may be the complete candidate, a portion, or an element ofthe candidate medical device. Similarly, a portion or an element of theanatomical features, not the entire anatomy scanned, may be received bythe Mesh Generator 130. The Medical Device Model may be created by acomputer-aided-design (CAD) software application and stored as a CADdata file. Examples of suitable CAD software packages include I-DEAS(available from SDRC, Inc. of Milford, Ohio) and CATIA (available fromInternational Business Machines Corporation), however, any othersuitable application could be used. The Medical Device Model could also,for example, be created through contact or non-contact three dimensionalmeasurement/imaging of a physical device or model. In anotherembodiment, the medical device model 140 is created within the MeshGenerator 130 module itself.

In addition, although the embodiment of FIG. 1 contemplates the use ofCT or MRI volumetric data 110 as input, volumetric input could also begenerated from any other suitable source, including other imaging systemsources such as ultrasound imaging systems, beta scan imaging,radionuclide scanning, thermography and the like. Anatomical volumetricinput data could also be artificially fabricated from idealized versionsof anatomical features, which may be initially obtained from CT-data andmodified, or be created manually by modeling such idealized version.These could be created to test medical devices within anatomicalfeatures having specified characteristics. For example, it may bedesirable to test a medical device in an aorta having two distendedsections caused by aortic aneurysms, which are separated by anon-distended portion of the aorta. Input data representing such ananatomical feature could be generated by manually entering data known towholly represent such an anatomical feature. Alternatively, input datarepresenting such an anatomical feature could be constructed by manuallyentering data corresponding to portions of CT, MRI or other imagingcreated data of actual patient aortas.

The output of the Mesh Generator 130 is then received by theStress/Strain/Deformation Analyzer 160. The Stress/Strain/DeformationAnalyzer 160 also receives Materials Model data 170 and Load data 150 asinput, which may also be outputs of the Mesh Generator 130. The outputof the Stress/Strain/Deformation Analyzer 160 comprises the medicaldevice performance data for evaluation, which may then be received bythe Visualization tool 180 as input. The Visualization tool 180 in turndisplays, through animation or visual representations, the predictedstresses, strains, and deformations on the candidate prosthesis“virtually in vivo.”

In an embodiment of the invention, the Geometry Generator 120 is acustom-developed software tool or the MIMICS software from MaterialiseNV (with offices in Ann Arbor, Mich., USA); the Mesh Generator 130 isTRUEGRID® of XYZ Scientific Applications, Inc. (Livermore, Calif., USA);the Stress/Strain/Deformation Analyzer 160 is a modified version ofNIKE3D or DYNA3D available from Lawrence Livermore National Laboratory(LLNL); and the Visualization tool 180 is the GRIZ visualizationsoftware, also developed by LLNL.

The unique combination of tools, data, and processing techniques asdescribed herein in conjunction with the preferred embodiment provides amore accurate in vitro representation of anticipated in vivo forcesexerted on medical devices and thereby reduces cost and time in thefabrication and testing of prototypes.

The various systems or components 120, 130, 160, 180, inputs (e.g., viafiles), and outputs (e.g., via files) of the present invention may becontained in one or in a plurality of computers. Thus, the GeometryGenerator may be contained in one computer, while theStress/Strain/Deformation Analyzer and the Visualization tool are runand contained in a separate computer. Furthermore, the inputs need notdirectly be received by the receiving system, e.g., through a networktransmission. The outputs for example, of the Geometry Generator may bestored in a floppy disk and read by a Mesh Generator via that floppydisk.

FIG. 2 shows the data flow for an embodiment of a Geometry Generator 120of FIG. 1 in detail. The Geometry Generator 120 receives as input the CTscan, MRI data, or other three-dimensional (3D) volumetric data 110. Itis preferred that data from CT scans or MRIs be used in this inventionbecause they provide a 3D volumetric representation of patient anatomyand blood vessel morphology, including complex atherosclerotic plaquedistribution within the flow lumen. This type of data thus provides anaccurate representation, for example, of the environment on which amedical device, for example, a TPEG will be placed. The CT and MRIequipment that is used to capture such 3D volumetric data are those thatare readily available.

Certain researchers and scientists in the biological sciences have attheir disposal a wealth of voxel data A voxel is the unit of CT or MRIreconstructions, represented as a pixel in the display of the CT scan orMRI. Well-established methods to extract triangular surfacerepresentations (hereinafter referred to “surface points”) from thesevoxel data using criteria such as variation in density are available. Anembodiment of the Geometry Generator 120 first extracts the surfacepoints, at step 220, from the CT scan or the MRI image data (e.g.,segmentation, contour based, or 3D approach). A CAD software is thenused to generate the Geometric Model 230 of the anatomy scanned usingthe extracted surface points. The extraction of surface points can beimplemented by writing a software program that implements the techniquesstated above or by available software programs. An example of a softwareprogram that generates surface points based on CT scan or MRI data isPREVIEW from Medical Media Systems.

The output of the Geometry Generator 120 is in the form of an AnatomyModel 240, which contains the geometric model of the anatomy scanned.The Anatomy Model 240 and the Medical Device Model 140 (containing thegeometric model of the candidate medical device) are then received bythe Mesh Generator 130 as input (usually as CAD files). The anatomymodel may be a portion or an element of the anatomy scanned. Similarly,the medical device model may be a portion or of an element of thecandidate medical device. This is useful for analyzing the interactionbetween a portion of a candidate device, such as a proximal stent in aTPEG, and a certain anatomical feature, such as tissue. The MeshGenerator 130 then generates a finite element model incorporating boththe anatomy model, whether idealized or actual, and the medical devicemodel as represented by box 250.

In one embodiment, the geometric models of the anatomy and the medicaldevice are created using CAD software. Generally, the geometric modelsare stored in the Initial Graphics Exchange Specification (IGES) formatthat is an industry-standard graphic file format for CAD systems.Because of its wide-use, many FEA software tools read and utilize theIGES format. In another embodiment, the geometric models are createddirectly in the Mesh Generator.

The Mesh Generator 130 in accordance with an embodiment of the inventionis TRUEGRID®. TRUEGRID is a 3-D finite modeling and analysis tool thatgenerates meshes or finite element models. It is a software thattessellates a geometric model into hexahedron brick elements andquadrilateral shell elements, creating a mesh or a grid. A FEA meshgenerating tool, such as TRUEGRID, uses the anatomy model 240 andmedical device model 140 created by a CAD software to generate a mesh.In another embodiment of a Geometry Generator 120 (not shown in thefigures), the Geometry Generator is a software tool that interfacesbetween scanner data, such as CT, MRI, and technical scanner data, andRapid Prototyping, CAD, or Finite Element analysis data. Such softwaretools typically generate surface points from such scanner data, whichare then converted into STL (stereolithography), slice files, and/orIGES files, which may then be read by the Mesh Generator 130 as input.An example of such a Geometry Generator 120 is the “MaterialiseInteractive Medical Image Control System” (MIMICS) available fromMaterialise, referred to above. The output of the MIMICS program, forexample, may be directly read and processed by the Mesh Generator 130.Thus, steps 220 and 230, illustrated in FIG. 2, are not necessarilyimplemented by this alternative embodiment of the Geometry Generator120.

FIG. 3 is a block diagram showing another embodiment of a virtualprototyping system 105. FIG. 3 is similar to FIG. 1, except that theanatomical feature is not obtained from a 3D volumetric data, such as aCT scan. Rather, an in vitro model of the anatomical feature ispresented for analysis. For example, instead of a CT-scan artery, thesystem analyzes the stresses, strains, and deformations of a medicaldevice deployed in a latex tube, which represents the artery or the invitro model. Such in vitro model may be a CAD file that is read by theMesh Generator 130 or in another embodiment created within the MeshGenerator itself. Alternatively, an idealized anatomical feature may becreated through this embodiment. In another embodiment of the invention,not shown in the figure, the system may do a component or elementanalysis of a proposed medical device, without the incorporation ofeither an anatomical feature or in vitro model.

FIG. 4 is a block diagram showing in detail the data flow of theStress/Strain/Deformation Analyzer 160, which preferably is a non-linearfinite element modeling software application such as DYNA3D or NIKE3D.The Stress/Strain/Deformation Analyzer receives a mesh incorporatingboth the medical device and the anatomy scanned (idealized or actual), amesh incorporating both the medical device and in vitro model, or a meshincorporating just the medical device model 250. A portion of themedical device, in vitro model, or the anatomy scanned may be used. TheStress/Strain/Deformation Analyzer 160 also receives the Materials Model170, and the Load 150 on the applicable structures (e.g., TPEG andartery or just on the medical device) to generate an output used by theVisualization tool 180. In the preferred embodiment, the Materials Model170 and the Load 150 are read by TRUEGRID through a command file(further discussed below). Thus, the outputs of TRUEGRID (the MeshGenerator) do not only include the finite element model 250 of the meshincorporating both medical device and anatomy scanned, meshincorporating both medical device and in vitro model, or a meshcontaining only the medical device, but the materials model 170parameters as well as load 150 information. This reduces the number ofcode changes, if necessary, within DYNA3D or NIKE3D, or the manual entryof input values to be read by DYNA3D or NIKE3D.

DYNA3D is a general-purpose, explicit, three dimensional, finite elementprogram for analyzing and simulating the large deformation dynamicresponse of inelastic solids and structures. DYNA3D and NIKE3D implementa number of material models, for example, including elastic, orthotropicelastic, and kinematics/isotropic plasticity. NIKE3D is ageneral-purpose nonlinear implicit, three-dimensional, finite elementprogram for analyzing and simulating the finite strain and static anddynamic response of inelastic solids, shells, and beams.

FEA Stress/Strain/Deformation Analyzers, such as DYNA3D and NIKE3D, arecapable of analyzing and simulating sliding interfaces, body force loadsdue to base acceleration, body force loads due to spinning(geometry-dependent), concentrated nodal loads, pressure boundaryconditions (geometry-dependent), and displacement boundary conditions.

The Materials Model 170 is the numerical representation of the materialcharacteristics of the medical device, the anatomy, and/or the in vitromodel being analyzed. Loads include pressures, displacement, forces, anddeformations. Using the mesh 250, the Materials Model 170, and the Load150, the Stress/Strain/Deformation Analyzer 160 then analyzes andsimulates the non-linear stress, strain, and deformation over time suchas on a medical device (e.g., a TPEG and the arterial wall). TheStress/Strain/Deformation Analyzer in accordance with an embodiment ofthe present invention utilizes non-linear analysis (e.g., usingnon-linear formulas) or linear analysis to simulate and to analyze thenon-linear static or dynamic behavior in the structure.

In FIG. 4, the Materials Model 170 is directly received by theStress/Strain/Deformation Analyzer 160. Another way to have thematerials model be received by the Stress/Strain/Deformation Analyzer160 is by modifying the source code of DYNA3D and NIKE3D, e.g., byhard-coding the materials model into the source code itself. Similarly,if the source code of the geometry generator, Mesh Generator,Stress/Strain/Deformation Analyzer, and/or Visualization tool areavailable, inputs as shown may be incorporated, for example, by actuallyhard-coding the input parameters into the source code or by changingcertain equations in the code itself.

Once the Stress/Strain/Deformation Analyzer 160 has analyzed thestresses, strains, and deformations on the medical device, theVisualization module 180 (in FIG. 1) can then receive the output of theStress/Strain/Deformation Analyzer to visually display the resultingstresses, strains, and deformations 190.

Generally, the numerical output of the Stress/Strain/DeformationAnalyzer 160 may also be analyzed to determine the stresses, strains,deformations on the medical device without using the Visualization tool180. Using the Visualization tool 180, however, facilitates suchdetermination because the stresses, strains, and deformations are shownvia a graphical and visual display. A virtual prototyping or simulationof a medical device design, rather than plain numerical output data, isthus produced.

In an embodiment, the Visualization tool 180 is provided by theabove-referenced GRIZ software application. GRIZ is an interactivesoftware for visualizing FEA results on three-dimensional unstructuredgrids, and calculates and displays derived variables from FEA softwaretools such as DYNA3D, NIKE3D, and TOPAZ3D (also developed by LLNL). GRIZprovides display control of the mesh materials on an individual basis,allowing the user to concentrate on the analysis and visually focus onimportant subsets of the mesh, and provides the ability to animate therepresentation over time.

GRIZ uses the Silicon Graphic Inc. (SGI) Graphics Library (GL) or OpenGL for rendering and the “Motif widget” toolkit for its user interface.In order to compile and run GRIZ, both of these libraries are required.GRIZ can be used on SGI workstations as well as on SUN and otherworkstations using commercial GL emulation software.

Considering the visual result on the screen display 190, a user may thencompare the candidate medical device as designed against selectedperformance requirements. If the selected design meets the performancerequirements, then a prototype of the selected medical device design maybe built and tested. In addition, the visual result on the screendisplay 190 can be used by a physician to aid in the selection ofvarious versions (e.g., sizes) of a given medical device design. Forexample, prior to a procedure for placement of a TPEG in a patient'saorta, the physician may first virtually test the performance of variousTPEG designs or various versions of a single TPEG design prior to theprocedure. To accomplish this, the physician would obtain volumetricdata from the patient's aorta by any of the various methods discussedabove and input that data into an embodiment of a system 105 (in FIG. 1)for analyzing the use of a medical device. The same or similar type ofvolumetric and materials data for a version of TPEG design to be testedis also loaded into the system 105. Note that it may be possible to loadvolumetric data from several anatomical features and versions of TPEGdesigns to be analyzed at one time, and then for the physician to choosewhich two to test together at a later time. Once the input data isloaded into the system 105, the visual result of the analysis of theStress/Strain/Deformation Analyzer 160 is viewed by the physician on thescreen display 190 and based on those results, the physician determineswhether the TPEG version tested meets, exceeds, or falls short of theclinical requirements of the patient.

If the version of the TPEG which was virtually tested by the system 105falls short of the clinical requirements of the patient, another versionmay be tested and so on until an appropriate design is identified. Thephysician may then begin the actual procedure on the patient with theappropriate TPEG design version. The system 105 may be configured todisplay the performance of a given TPEG design version with regard tolong term structural integrity, prevention of perigraft leaks or sealingfunction, the general sizing of the TPEG with respect to the patient'saorta and the like. With regard to testing of the long term durabilityor structural integrity of the TPEG or other medical device design, thesystem 105 has great utility. Specifically, system 105 has the ability,assuming the use of sufficiently powerful CPUs, to recreate largenumbers of cyclic expansions and contractions in a short period of time.For example, as discussed above, the vascular system of a patient isconstantly expanding and contracting as a result of dynamic or staticpressure gradients within the vasculature from the patient's beatingheart. These expansions and contractions can put stresses, strains, anddeformations on intracorporeal medical devices, such as TPEG, which overtime can lead to failure of the device. System 105 would give thephysician the ability to quickly test a chosen TPEG design in a virtualmodel of the patient's expanding and contracting aorta for an amount ofcycles that would equal or exceed the amount of cycles that would beexpected in the patient's lifetime to determine the long term safety andefficacy of the design choice. Of course, a similar time compressedanalysis could be used for any other type of medical device in any otherpart of a patient's body. Accordingly, if the invention is used as apreprocedure tool, physicians may analyze the use of various TPEGembodiments and select those that meet their performance requirementsthereby allowing the physicians to select the best medical devices, suchas the best TPEGs for treating their patients with aneurysm.

Because of the computing resources needed by FEA software tools, theyare generally run on Silicon Graphics or other UNIX computer systems.The Mesh Generator, Stress/Strain/Deformation Analyzer, and thevisualization of the stresses, strains, and deformations on thecandidate TPEG have been run on a Silicon Graphics (R12000) machine with640 MB of memory.

Modifications to DYNA3D or NIKE3D

In one embodiment, NIKE3D and DYN/A3D were used and modified toimplement the features of the present invention (TPEG design wasanalyzed). In determining the required material model, an exemplarymaterial model (herein called TPEG material model (W)) was used toaccommodate a strain energy density of the form:W=a ₁₀(I ₁−3)+a ₀₁(I ₂−3)+a ₂₀(I ₁−3)² +a ₁₁(I ₁−3)(I ₂−3)+a ₀₂(I ₂−3)²+a ₃₀(I ₁−3)+a ₂₁(I ₁−3)²(I ₂−3)+a ₁₂(I ₁−3)(I ₂−3)² +a ₀₃(I ₂−3)³+½K(I₃−1)²with K=2(a ₁₀ +a ₀₁)/(1−2ν)

where

-   -   a_(ij) are material parameters;    -   ν is Poisson's ratio;    -   K is the bulk modulus given as a function of Poisson's ratio;        and    -   I₁, I₂, and I₃ are the first, second, and third invariants of        the right Cauchy-Green strain tensor, respectively.

The TPEG material model (W), discussed above, was derived from adoctoral thesis, which discusses the stress in abdominal aorticaneurysm. (See Madhavan Lakshmiraghavan, Mechanical Wall Stress inAbdominal Aortic Aneurysm: Towards Development of a Clinical Tool toPredict Aneurysm Rupture (1998) (unpublished Ph.D. dissertation,University of Pittsburgh which is hereby incorporated herein in itsentirety).

Other articles discussing a hyperelastic material, linear elastic, andnon-linear elastic models of the aortic walls may also be used to derivea material model as exemplified above and other applications of thevirtual prototyping system 105 (in FIG. 1). (See M. L. Raghavan et al.,Ex Vivo Biomechanical Behavior of Abdominal Aortic Aneurysm: AssessmentUsing a New Mathematical Model, 24 Annals of Biomedical Engineering573-582 (1996); David A. Vorp. Et al., Finite Element Analysis of theEffect of Diameter and Asymmetry on the Wall Stress Distribution inAbdominal Aortic Aneurysm, 35 BED (Bioengineering Conference ASME 1997)33-34 (1997), both of which are incorporated by reference herein intheir entirety).

Modifications to NIKE3D

NIKE3D has an existing material model, number 15, which is athree-dimensional continuum hyperelastic material that uses a strainenergy density function of the form:

W = A(I₁ − 3) + B(I₂ − 3) + 1/2K(ln  θ)² with$K = \frac{4\left( {A + B} \right)\left( {1 + v} \right)}{\left( {3 - {6v}} \right)}$

where

-   -   A and B are material parameters;    -   ν is Poisson's ratio;    -   K is the bulk modulus given as a function of Poisson's ratio;    -   I₁ and I₂ are the first and second invariants of the right        Cauchy-Green strain tensor, respectively; and    -   θ is the current volume of the element divided by the undeformed        volume.

Using the material model 15 as the framework, the material model 15 ismodified to implement the TPEG Material Model “W” listed above. Thisentails ensuring that variables are accordingly updated or modified inthe source code to capture the information required by the TPEG MaterialModel. Material model 15 was chosen from the NIKE3D models because itinvolves the least amount of code modification to implement the featuresof the present invention.

Implementation of the TPEG Material Model in NIKE3D

To implement the features in accordance with the present invention, twoNIKE3D subroutines, weval.f and printm.f, were modified.

The following modifications were made to NIKE3D subroutine weval.f:

-   -   a) Ten material parameters (a₁₀, a₀₁, a₂₀, a₁₁, a₀₂, a₃₀, a₂₁,        a₁₂, a₀₃, K) were read instead of three (A, B, and K).    -   b) The calculation of K was changed from K=4(A+B)(1+ν))/(3−6ν)        to K=2(a₁₀+a₀₁)/(1−2ν)    -   c) The calculation of

$\frac{\partial W}{\partial I_{1}}$was changed from

$\frac{\partial W}{\partial I_{1}} = {{A\mspace{14mu}{to}\mspace{14mu}\frac{\partial W}{\partial I_{1}}} = {a_{10} + {2{a_{20}\left( {I_{1} - 3} \right)}} + {a_{11}\left( {I_{2} - 3} \right)} + {3{a_{30}\left( {I_{1} - 3} \right)}^{2}} + {2{a_{21}\left( {I_{1} - 3} \right)}\left( {I_{2} - 3} \right)} + {a_{12}\left( {I_{2} - 3} \right)}^{2}}}$

-   -   d) The calculation of

$\frac{\partial W}{\partial I_{2}}$was changed from

$\frac{\partial W}{\partial I_{2}} = {{B\mspace{14mu}{to}\mspace{14mu}\frac{\partial W}{\partial I_{2}}} = {a_{01} + {a_{11}\left( {I_{1} - 3} \right)} + {2a_{02}\left( {I_{2} - 3} \right)} + {a_{21}\left( {I_{1} - 3} \right)}^{2} + {2{a_{12}\left( {I_{1} - 3} \right)}\left( {I_{2} - 3} \right)} + {3{a_{03}\left( {I_{2} - 3} \right)}^{2}}}}$

-   -   e) The higher derivatives of W with respect to I₁ and I₂ were        changed from zero to

${\frac{\partial^{2}W}{\partial I_{1}^{2}} = {{2a_{20}} + {6{a_{30}\left( {I_{1} - 3} \right)}} + {2{a_{21}\left( {I_{2} - 3} \right)}}}},{\frac{\partial^{2}W}{\partial I_{2}^{2}} = {{2a_{02}} + {2{a_{12}\left( {I_{1} - 3} \right)}} + {6{a_{03}\left( {I_{2} - 3} \right)}}}},{and}$$\frac{\partial^{2}W}{{\partial I_{1}}{\partial I_{2}}} = {a_{11} + {2{a_{21}\left( {I_{1} - 3} \right)}} + {2{a_{12}\left( {I_{2} - 3} \right)}}}$

-   -   f) The derivatives with respect to I₃ were changed from

$\frac{\partial W}{\partial I_{3}} = {{K\left( {\ln\;{I_{3}/I_{3}}} \right)}\mspace{14mu}{to}}$${\frac{\partial W}{\partial I_{3}} = {{K\left( {I_{3} - 1} \right)}\mspace{14mu}{and}\mspace{14mu}{from}}}\;$$\frac{\partial^{2}W}{\partial I_{3}^{2}} = {{{K\left( {\left( {1 - {\ln\; I_{3}}} \right)/I_{3}^{2}} \right)}\mspace{14mu}{to}\mspace{14mu}\frac{\partial^{2}W}{\partial I_{3}^{2}}} = K}$

-   -   g) When a completely incompressible material (I₃=1) is specified        by setting the augmented Lagrangian flag to true, the        derivatives with respect to I₃ are left in the log form. The log        form shows substantially faster convergence and better stability        for completely incompressible materials.

The NIKE3D subroutine printm.f was modified to print out all nine amaterial parameters to the material description in the high-speedprintout file.

Invocation of the Modified NIKE3D TPEG Material Model

The TPEG material model (W) (i.e., the modified NIKE3D Material Model15) is invoked in NIKE3D using the input data format shown in Table I.Poisson's ratio is kept as the third parameter to maintain compatibilitywith models using the original NIKE3D hyperelastic model. Thedocumentation for NIKE3D, and the TRUEGRID Mesh Generator, provides aninput format list for Material Model 15 similar to Table I given below,with A, B, and ν all defined on card 3 (it should be understood that the“card” represents lines of input data). The original NIKE3D code,however, reads A from columns 1-10 card 3, B from columns 1-10 of card4, and ν from columns 1-10 of card 5. This format was changed to complywith the NIKE3D manual and the format in Table I in the modified weval.fand printm.f subroutines.

TABLE I Input parameters format for the modified NIKE3D material model(TPEG material model) Card Columns Description Format 1 1-5 Material IDnumber I5 1  6-10 Material type (use 15) I5 1 11-20 Density E 10.0 121-25 Element class (not used) I5 1 26-35 Reference temperature (notused) E 10.0 1 36-45 Rayleigh damping parameter alpha E 10.0 1 46-55Rayleigh damping parameter beta E 10.0 2  1-72 Material title 12A6 3 1-10 a₁₀ E 10.0 3 11-20 a₀₁ E 10.0 3 21-30 Poisson's ratio E 10.0 331-40 a₂₀ E 10.0 3 41-50 a₁₁ E 10.0 3 51-60 a₀₂ E 10.0 3 61-70 a₃₀ E10.0 3 71-80 a₂₁ E 10.0 4  1-10 a₁₂ E 10.0 4 11-20 a₀₃ E 10.0 5-7 AllBlank 8  1-10 Augmented Lagrangian flag E 10.0 .EQ.1: active, enforcecompressibility with augmented Lagrangian iteration 8 11-20 Convergencetolerance for E 10.0 augmented Lagrangian iteration .GT.0.0: convergedwhen volume strain norm < TOL (tolerance) .LT.0.0: augment exactly - TOLtimes

The format column specifies the expected data type. For example, aformat of “I” means that an integer is expected (“I5” means integer with5 positions), “E” means a real numeric value, and “A” means characterdata type.

Modifications to DYNA3D

DYNA3D has an existing material model number 27, which is athree-dimensional continuum hyperelastic material that uses a strainenergy density function of the form

W = A(I₁ − 3) + B(I₂ − 3) + C(I₃² − 3) + D(I₃ − 3)² with C = 1/2A + Band$D = \frac{{A\left( {{5v} - 2} \right)} + {B\left( {{11v} - 5} \right)}}{2 - {4v}}$

where:

-   -   A and B are material parameters;    -   ν is Poisson's ratio; and    -   I₁, I₂, and I₃ are the first, second, and third invariants of        the right Cauchy-Green strain tensor, respectively.

The material model 27 may be modified to implement the TPEG MaterialModel (W)). This also entails ensuring that variables are accordinglyupdated or modified in the source code to capture the information forthe TPEG material model (W).

Implementation of the TPEG Material Model in DYNA3D

To implement the features in accordance with the present invention, twoDYNA3D subroutines, f3dm27.f and printm.f, were modified. The “C(I₃⁻²−1)” term was left in the modified material model since without it,the explicit time integrator becomes unstable very easily. This termonly significantly changes the result when the material undergoessignificant change in volume. If ν≈0.5, the material behaves in a nearlyincompressible matter, in this case D is much larger than C, and theinclusion of C has little to no effect on the final result.

The following modifications were made to DYNA3D subroutine f3dm27.f:

-   -   a) Ten material parameters (a₁₀, a₀₁, a₂₀, a₁₁, a₀₂, a₃₀, a₂₁,        a₁₂, a₀₃, K) were read instead of four (A, B, C, and D).    -   b) The calculation of D was changed from        D=(A(5ν−2)+B(11ν−5))/(2−4ν) to D=(a₁₀+a₀₁)/(1−2ν)    -   c) The computation for I₁ and I₂ were added.    -   d) The calculation of

$\frac{\partial W}{\partial I_{1}}$was changed from

$\frac{\partial W}{\partial I_{1}} = {{A\mspace{14mu}{to}\mspace{14mu}\frac{\partial W}{\partial I_{1}}} = {a_{10} + {2{a_{20}\left( {I_{1} - 3} \right)}} + {a_{11}\left( {I_{2} - 3} \right)} + {3{a_{30}\left( {I_{1} - 3} \right)}^{2}} + {2{a_{21}\left( {I_{1} - 3} \right)}\left( {I_{2} - 3} \right)} + {{a_{12}\left( {I_{2} - 3} \right)}^{2}.}}}$

-   -   e) The calculation of

$\frac{\partial W}{\partial I_{2}}$was changed from

$\frac{\partial W}{\partial I_{2}} = {{B\mspace{14mu}{to}\mspace{14mu}\frac{\partial W}{\partial I_{2}}} = {a_{01} + {a_{11}\left( {I_{1} - 3} \right)} + {2a_{02}\left( {I_{2} - 3} \right)} + {a_{21}\left( {I_{1} - 3} \right)}^{2} + {2{a_{12}\left( {I_{1} - 3} \right)}\left( {I_{2} - 3} \right)} + {3{{a_{03}\left( {I_{2} - 3} \right)}^{2}.}}}}$

-   -   f) The calculation of

$\frac{\partial W}{\partial I_{3}} = {{2{D\left( {I_{3} - 1} \right)}} - {2{C\left( {I_{3}^{- 3} - 1} \right)}}}$remains unchanged, however, the value of D has changed.

The DYNA3D subroutine printm.f was modified to correctly output thehyperelastic material constants to the resulting high-speed printoutfile.

Invocation of the Modified DYNA3D Material Model (TPEG Material Model)

The TPEG material model (i.e., the modified DYNA3D material model 27) isinvoked in DYNA3D using the input data format shown in Table II.Poisson's ratio is kept as the third parameter to maintain compatibilitywith models using the original DYNA3D hyperelastic model.

TABLE II Input parameters format for the modified DYNA3D material model(TPEG material model) Card Columns Description Format 1 1-5 Material IDnumber I5 1  6-10 Material type (use 15) I5 1 11-20 Density E 10.0 121-25 Element class (not used) I5 1 26-35 Reference temperature (notused) E 10.0 1 36-45 Rayleigh damping parameter alpha E 10.0 1 46-55Rayleigh damping parameter beta E 10.0 2  1-72 Material title 12A6 3 1-10 a₁₀ E 10.0 3 11-20 a₀₁ E 10.0 3 21-30 Poisson's ratio E 10.0 331-40 a₂₀ E 10.0 3 41-50 a₁₁ E 10.0 3 51-60 a₀₂ E 10.0 3 61-70 a₃₀ E10.0 3 71-80 a₂₁ E 10.0 4  1-10 a₁₂ E 10.0 4 11-20 a₀₃ E 10.0 5-7 AllBlank

Reading the doctoral thesis mentioned above, the appropriate values ofinput parameters may accordingly be provided as input to theStress/Strain/Deformation Analyzer (see Madhavan Lakshmiraghavan,Mechanical Wall Stress in Abdominal Aortic Aneurysm: Towards Developmentof a Clinical Tool to Predict Aneurysm Rupture (1998) (unpublished Ph.D.dissertation, University of Pittsburgh).

TRUEGRID Command File

FIGS. 5A through 5M contain a command file that is an exemplary fileread by TRUEGRID to implement the features of the present invention(e.g., for stent design). This exemplary command file illustrates acomponent-level analysis of a stent, without the option for simulatingdeployment into CT-based anatomy (isim mode=6, not present in thecommand file).

TRUEGRID, in its basic form, is not only a Mesh Generator, but is also aformat generator. It outputs data in a certain format, which are thenread by NIKE3D and/or DYNA3D. The invention utilizes both TRUEGRID'scapability as a Mesh Generator and an output generator to create anoutput file (e.g., Tables I and II discussed above), containing theappropriate values that would be read by NIKE3D and DYNA3D,respectively. The outputs created by TRUEGRID may be created by othermeans, e.g., by other Mesh Generator software or proprietary software.

The command file (contained in FIGS. 5A-5M) contains the parameters andthe instructions that are read by TRUEGRID to generate the mesh and theoutput file(s), which are read by DYNA3D and/or NIKE3D.

The line numbers at the start of each line are only added to facilitatereference to particular lines in the command file and are not part ofthe command file. Text after the “c” are ignored by TRUEGRID (comments).To take advantage of the capabilities of TRUEGRID, the command filecontains various parameters that help developers customize theirsimulation and/or Stress/Strain/Deformation analysis. Mesh generatingtools, such as TRUEGRID, in the non-interactive mode, generally requirethat command files or similar files be created to enable them togenerate finite element models. In the interactive mode, a finiteelement model may be created by a medical device designer (e.g., TPEGdesigner) using the options available in the interactive mode ofTRUEGRID.

Referring to FIG. 5A, the inike parameter (lines 5 and 21) tellsTRUEGRID that the output file is to be read by a NIKE3DStress/Strain/Deformation Analyzer. The command file also tells TRUEGRIDthat the stent to be modeled is a full 3-segment stent design (line 6and 22), the model is a full 360 degree model of a stent (lines 6 and23), to model the stress on the initial expansion of the stent in vivo(lines 16 and 24), and to refine the elements by 2 in each direction ofthe cross section (lines 18 and 25). (Crowns can be a pointed or barbedportion of a stent—see lines 7 through 9). The command file thus enablesTRUEGRID to generate a mesh and a model of a stent subjected to variouscomponent-level in vitro tests such as radial force and predeliverycompression. Simulation of these tests enables a designer to refine andoptimize the stent design for its intended application (e.g. ascomponent of a TPEG or for treating occlusive disease).

TRUEGRID can also act like an interpreter. It reads the informationcontained in the command file, and interprets and processes the linesaccordingly. For example, the text after the word “para” or “parameter”are parameters read by TRUEGRID. These terms indicate the value or theformula that should be used by TRUEGRID. For example, line 21 denotesthat the parameter inike contains the initial value 1.

Line 46 in FIG. 5B means that the value of the parameter dCIA3 containsthe value 0.0.

Line 138 in FIG. 5D indicates that the initial value of the parameterrocompcyl is the value evaluated by the formula “[0.95*(min(% RCyl3,%RCyl6,% RCyl12_(—)1,% RCyl12_(—)2)−% RW6).” TRUEGRID understands thatthe min function has to be evaluated. The min function compares thevalue contained in each variable, in this case, contained in RCyl3(e.g., contains 1), RCyl6 (contains 0.005), RCyl12_(—)1 (contains0.987), and RCyl12_(—)2 (contains 0.0002), and returns the content ofthe variable, which holds the least value—0.0002 (value contained inRcyl12_(—)2). Assuming the variable RW6 contains the value 0.18,TRUEGRID then evaluates the rocompcly variable to contain0.95*0.0002−0.18, which equals to negative 0.17981. This value is thusthe initial value of rocompcyl when initially processed and read byTRUEGRID.

Embodiments of the invention can simulate various phases of TPEG use.For example, it calculates the stresses, strains, and deformations onthe TPEG when it is compressed then decompressed for deployment, whenthe TPEG is compressed into the catheter for deployment, when the TPEGexpands, and the like.

Referring to line 432, in FIG. 5L, the term “include” indicates toTRUEGRID that when the condition as defined in line 431 is met, theistent.mts_nike_solid file is read. The contents of this include filecould be added in the command file itself. For flexibility andreadability, however, they were placed in a separate file. Programmerstypically use include files, such as done in C or C++, for code controland ease of maintenance

FIGS. 6A-6F contain an exemplary text of a command file called“seal.run” (line 2) read by TRUEGRID for a simulated TPEG graftdeployment in a proximal aortic neck to generate a mesh incorporatingboth an anatomical feature and medical device and to output files thatare read by a Stress/Strain/Deformation Analyzer.

FIGS. 7A-7C is an exemplary include file, called “tpeg.part_ct_aorta3,”used by “seal.run” command file listed in FIGS. 6A-6F. See line 217 ofFIG. 6F. This file contains the commands which read in surfaces createdby the Geometry Generator 120 from CT data for the aorta and builds themesh for the vessel.

FIGS. 8A-8L is another exemplary command file read by TRUEGRID used inthe virtual prototyping system of the present invention for simulatingstent deployment into an anatomy from CT-data, as opposed to a stentgraft. The stent could be a part of a stent graft, could be intended foruse to treat occlusive disease in the vasculature, or could even be usedfor nonvascular application, such as an esophageal stent.

The files listed in FIGS. 5A-5M, 6A-6F, 7A-7C, and 8A-8L are written tobe read by TRUEGRID. Variations on such files are expected depending onthe Mesh Generator 130 deployed in the system.

FIG. 9A illustrates a flow chart, which sets forth the basic componentsof an embodiment of the inventive system and process in accordance withthe present invention. In particular, this figure illustrates how todevelop better-designed TPEGs. The steps illustrated may of course beutilized for developing other medical devices, other than TPEGs.

To start, a TPEG designer first determines, in box 905A, the performancerequirements desired, such as to secure an optimal structural integrityof the TPEG, to avoid potential health risks such as ruptures andendoleaks, or to have a smaller TPEG packaging. 3D volumetric data ofthe anatomy desired, for example, in this case a blood vessel, is thenacquired at box 910A, using CT or MRI scanners. Alternatively, if 3Dvolumetric data are already available, such acquisition may be skippedand such 3D volumetric data be obtained from the archive.

It should be noted here that the “anatomy” desired, which defines theembodiment in which a medical device is to be tested, is not necessarilylimited to a patient's body. For example, embodiments of the presentinvention could be used to obtain test results for medical deviceperformance in a wide variety of in vitro tests, some of which may benecessary or desirable for Food and Drug Administration (FDA) approvalof the medical device in question. Various forms of in vitro failuremode testing such on tensile pull testing and the like could beperformed by an embodiment of the invention and allow the tester toeasily vary test parameters, device design, and test frequency toquickly obtain the desired test results. In addition, volumetricanatomical data for animals could be used to simulate animal testingthat is necessary or desirable for FDA approval of a medical device.This may be of particular importance for a medical device design, whichseeks to establish equivalence with an existing approved product whichhas been previously tested in animal studies.

The geometry generator (120 in FIG. 1) then generates a blood vesselgeometric model in box 920A. As discussed above, the blood vesselgeometric model may be an actual idealized or in vitro model. If thegeometry generator is an embodiment where surface points are firstextracted, a CAD system may then be used to generate such geometricmodel.

Next, a candidate TPEG model or design, which is obtained typically froma model created using a CAD software, is selected or modeled by the TPEGdesigner (step 925A). The Mesh Generator (130 in FIG. 1) then generatesa mesh model incorporating both the blood vessel and the TPEG (930A). ATPEG designer then determines the material properties of the candidateTPEG model and the blood vessel at step 935A. The material propertiesmay also have been assigned by the TPEG designer during the previousstep (i.e., the generation of the mesh model). Using aStress/Strain/Deformation Analyzer (160 in FIG. 1), assuming that theload (150 in FIG. 1) and the Materials Model (170 in FIG. 1) areavailable to the Stress/Strain/Deformation Analyzer for input, a TPEGdesigner then simulates the candidate TPEG design behavior in astress/strain/deformation analysis (at step 940A) to determine if thecandidate TPEG meets the performance requirements.

If the candidate TPEG does not meet the performance requirements, a“no.” outcome at decision box 955A, the TPEG designer chooses anotherTPEG design or model at step 980A, and repeats the steps as shown by thearrow to box 925A. If it, however, meets the target performancerequirements, a “yes” outcome at decision box 955A, a prototype is thenfabricated based on the candidate TPEG model and design at step 960A.The fabricated prototype is then subjected to testing, e.g., animaltesting or clinical testing, at step 965A. If the fabricated prototypemeets the target performance requirements, the candidate TPEG model thusis a final design and may be used to produce other TPEGs.

If the fabricated prototype, however, does not meet the performancerequirements, a “no” outcome at decision box 970A, the TPEG designermodifies the TPEG design or selects a new TPEG design, and repeats thesteps as shown with the arrow to box 925A. If necessary, the process isrepeated several times until the performance requirements and the finaldesign is obtained. A benefit of the invention is to reduce the numberof “no” outcome at decision box 970A compared to a development processwhich uses only hardware prototypes for design verification.

As discussed above, a proposed TPEG model may be evaluated against anumber of anatomical features to determine the suitable range ofconditions of an applicable TPEG model (e.g., size). Similarly, a set ofanatomical features may be evaluated against a number of TPEG models todetermine the type of suitable TPEG model for such set of anatomicalfeature. Furthermore, an analysis of the stresses, strains, anddeformations may be conducted on the medical device without interactionto certain anatomical features.

FIG. 9B, is similar to FIG. 9A except for the additional step (box 942B)of displaying the visual simulation of the stresses and strains on theTPEG. The display of the simulation is typically employed using theVisualization tool (180 in FIG. 1), which in the preferred embodiment isthe GRIZ software.

Visual display of the simulation is not necessary because a reading ofthe numerical representation of the stresses, strains, and deformationon the TPEG may guide a TPEG designer whether the performancerequirements are met. However, visual display is often desirable becausea visual representation of the stresses and strains, for example, redhot spots on the visual TPEG model can be easier to understand than merenumerical representations.

FIG. 10 is similar to FIG. 9A and illustrates a process to developbetter-designed medical devices using in vitro features. In the firststep as shown in 1005, a medical device designer, determines theperformance requirements. The next step is to generate a geometry modelof the in vitro model, step 1020A, (e.g., latex tube to represent anartery), using software tools, such as a CAD software or even TRUEGRID.The steps are then similar to those illustrated in FIG. 9A. In anotherembodiment, the in vitro model such as a latex tube may be scanned toobtain a 3D volumetric data Such acquired 3D volumetric data may also bemodified by the medical device designer.

In another embodiment not shown, only the medical device model isanalyzed absent the anatomical feature or in vitro model. The operationsshown in FIG. 10 would be implemented, without the operation ofgenerating blood vessel geometric model (step 1020A) and the analysiswould only be performed on the geometric model of the candidate medicaldevice or a potion of it. Material properties and load informationpertinent only to the medical device are generally used in the analysisprocess.

FIG. 11 contains steps similar to those illustrated in FIG. 9A. FIG. 11illustrates an embodiment of the present invention as a preprocedureplanning tool, for example, to guide a physician in deciding whichparticular TPEG to implant in a patient.

To start, a physician first determines, in box 1105, the surgical orinterventional procedure objectives, typically, to ensure robust sealingand structural integrity of the TPEG in vivo for a particular patient.The physician then obtains 3D volumetric data of the potential site ofthe TPEG, e.g., the abdominal aorta, at step 1110. The GeometryGenerator (120 in FIG. 1) then extracts the surface points from the 3Dvolumetric data acquired in step 1115. Based on the surface pointsextracted, a blood vessel geometric model is created 1120.

Next, a candidate TPEG, which is obtained typically from a model createdusing a CAD software, is selected by the physician (step 1125). (TPEGmodels may be created in advance and stored in a library in the system.At this point, the physician is determining which available TPEG designis best suited for that patient or individual). The Mesh Generator (130in FIG. 1) then generates a mesh model incorporating both the bloodvessel and the selected TPEG. A physician may then identify the materialproperties of the candidate TPEG and the blood vessel at step 1135. Thematerial properties may have also been assigned during the previous step(i.e., the generation of the mesh model). Using aStress/Strain/Deformation Analyzer (160 in FIG. 1), assuming that theload (150 in FIG. 1) and the materials model (170 in FIG. 1) areavailable to the Stress/Strain/Deformation Analyzer for input, aphysician may then run the candidate TPEG to a stress/strain/deformationanalysis (at step 640) to determine if the candidate TPEG meets thesurgical objectives.

If the candidate TPEG does not meet the procedural objectives, a “no”outcome at decision box 1155, a physician may decide to change the TPEGto be used in the procedure at step 1180 and repeat the process as shownby the arrow to box 1125. Based on the physician's judgment, if thecandidate TPEG does meet the procedural objectives, a “yes” outcome atdecision box 655, the physician then may decide whether to proceed withthe planned TPEG implant procedure or not, at step 1160.

FIG. 12 contains a representation of one simulation display of a cutawaylateral view of a vascular stent in the infrarenal aorta just proximalto an abdominal aneurysm. Using the system as described above, severaldisplays may be presented to the user showing the progressive stentexpansion and contact with the luminal surface of the vessel. The systemmay be also be used such that the visualization module displays themedical device and the anatomical feature in color, with colors andtheir gradients representing the various stresses, strains, anddeformations on the medical device and the anatomical feature. Otherviews, such as a proximal view, may also be used in simulation. FIG. 13is a block diagram of an exemplary computer 1300 such as might compriseany of the computers containing a Geometry Generator 120, a MeshGenerator 130, a Stress/Strain/Deformation Analyzer 160, and aVisualization tool 180. Each computer 1300 operates under control of acentral processor unit (CPU) 1302, such as a high-end microprocessor,e.g., typically found in Silicon Graphics workstation, and associatedintegrated circuit chips. A computer user can input commands and datafrom a keyboard and mouse 1312 and can view inputs and computer outputat a display 1310. The display is typically a video monitor or flatpanel display device. The computer 1300 also includes a direct accessstorage device (DASD) 1304, such as a fixed hard disk drive. The memory1306 typically comprises volatile semiconductor random access memory(RAM). Each computer preferably includes a program product reader 1314that accepts a program product storage device 1316, from which theprogram product reader can read data (and to which it can optionallywrite data). The program product reader can comprise, for example, adisk drive, and the program product storage device can compriseremovable storage media such as a floppy disk, an optical CD-ROM disc, aCD-R disc, a CD-RW disc, DVD disk, or the like. In the preferredembodiment, each computer 1300 can communicate with the other connectedcomputers over the network 1320 through a network interface 1308 thatenables communication over a connection 1318 between the network and thecomputer. This facilitates having each separate system as illustrated inFIG. 1, provide inputs and outputs to the other components in thesystem.

The CPU 1302 operates under control of programming steps that aretemporarily stored in the memory 1306 of the computer 1300. When theprogramming steps are executed, the pertinent system component performsits functions. Thus, the programming steps implement the functionalityof the system components illustrated in the figures. The programmingsteps can be received from the DASD 1304, through the program product1316, or through the network connection 1318. The storage drive 1304 canreceive a program product, read programming steps recorded thereon, andtransfer the programming steps into the memory 1306 for execution by theCPU 1302. As noted above, the program product storage device cancomprise any one of multiple removable media having recordedcomputer-readable instructions, including magnetic floppy disks, CD-ROM,and DVD storage discs. Other suitable program product storage devicescan include magnetic tape and semiconductor memory chips. In this way,the processing steps necessary for operation in accordance with theinvention can be embodied on a program product.

Alternatively, the program steps can be received into the operatingmemory 1306 over the network 1318. In the network method, the computerreceives data including program steps into the memory 1306 through thenetwork interface 1308 after network communication has been establishedover the network connection 1318. The program steps are then executed bythe CPU 1302 to implement the processing of the present invention.

Although the present invention is implemented on UNIX workstations,typical personal computers could likely be adopted to perform thesefunctions in the future.

It should be understood that all of the computers of the systemsembodying the various systems illustrated in FIG. 1, preferably have aconstruction similar to that shown in FIG. 13, so that details describedwith respect to the FIG. 13 computer 1300 will be understood to apply toall computers or components of the system. Any of the computers can havean alternative construction, so long as they have sufficient resourcesand processing power to handle finite element analyses and otherfunctions in accordance with the present invention.

Those skilled in the art will recognize that variations in the steps, aswell as the order of execution, may be done and still make the variousembodiments of the invention operate. Furthermore, one skilled in theart will realize that although the examples described herein generallyrefer to TPEGs, other medical devices may be designed in accordance withthe present invention.

In addition, although the modules of the system 105 (FIG. 1), theGeometry Generator, the Mesh Generator, Stress/Strain/DeformationAnalyzer, and the Visualization module, are shown in different boxes,depending on the software tools utilized their functions may with eachother. Some functions, for example, that are done by one module, e.g.,the Mesh Generator, TRUEGRID, thus, may also be done by the GeometryGenerator, MIMICS, or vice versa.

Embodiments of the present invention have been described above so thatan understanding of the present invention can be conveyed. There are,however, many alternative software programs available or able to bewritten that would embody the functions of the present invention, andthus, may be used accordingly. The present invention should thereforenot be seen as limited to the particular embodiments described herein,but rather, it should be understood that the present invention has wideapplicability with respect to medical device design generally. Allmodifications, variations, or equivalent arrangements andimplementations that are within the scope of the attached claims shouldtherefore be considered within the scope of the invention.

1. A computer system including at least one processor and memory foranalyzing medical devices comprising: a geometry generator that receivesthree-dimensional volumetric data of at least one anatomical feature(s)and generates a geometric model of said anatomical feature(s); a meshgenerator that receives said geometric model of said anatomicalfeature(s) and a geometric model of a medical device, and generates afinite element model representing both of said geometric model of saidanatomical feature(s) and said geometric model of said medical device;and a stress/strain/deformation analyzer that receives said finiteelement model, material properties of said anatomical feature(s) andsaid medical device, load data on said anatomical feature(s) and/or saidmedical device and simulates an interaction between said anatomicalfeature(s) and said medical device over at least one dynamic expansionand contraction cycle of the anatomical feature(s) to determinepredicted stresses, strains, and deformations of said medical device dueto the interaction of the medical device with the anatomical feature(s).2. The system of claim 1 wherein said geometric model of said anatomicalfeature(s) is an idealized geometric model.
 3. The system of claim 1wherein said three-dimensional volumetric data are acquired via CT scan.4. The system of claim 1 wherein said three-dimensional volumetric dataare acquired via MRI.
 5. The system of claim 1 wherein said geometrygenerator is a software application which generates surface points fromthe three-dimensional volumetric data, which are then converted intostereolithography, slice files, ICES files or a combination thereof. 6.The system of claim 1 wherein said mesh generator includesthree-dimensional finite modeling software.
 7. The system of claim 1wherein said stress/strain/deformation analyzer is a non-linear finiteelement modeling software application.
 8. The system of claim 6 whereinsaid three dimensional finite modeling software tessellates a geometricmodel into hexahedron brick elements and quadrilateral shell elements tocreate the finite element model.
 9. The system of claim 7 wherein saidnon-linear finite element modeling software application is configured toaccommodate a strain energy density of the form:W=a ₁₀(I ₁−3)+a ₀₁(I ₂−3)+a ₂₀(I ₁−3)² +a ₁₁(I ₁−3)(I ₂−3)+a ₀₂(I ₂−3)²+a ₃₀(I ₁−3)+a ₂₁(I ₁−3)²(I ₂−3)+a ₁₂(I ₁−3)(I ₂+3)² +a ₀₃(I ₂−3)³+½K(I₃−1)²with K=2(a ₁₀ +a ₀₁)/(1−2v) where a_(ij) are material parameters; v isPoisson's ratio; K is the bulk modulus given as a function of Poisson'sratio; and I₁, I₂, and I₃ are first, second, and third invariants of aright Cauchy-Green strain tensor, respectively.
 10. The system of claim1 further comprising a visualization tool that receives said simulatedstresses, strains, and deformations of said medical device from saidstress/strain/deformation analyzer and displays one or more of saidstresses, strains, and deformations of said medical device via visualrepresentation.
 11. The system of claim 10 wherein said visualizationtool includes interactive software for visualizing finite elementanalysis results of three-dimensional grids.
 12. A computer implementedmethod for analyzing a medical device comprising: acquiringthree-dimensional volumetric data of at least one anatomical feature ofa patient; generating a geometric model of said anatomical feature(s);receiving data representing a geometric model of a candidate medicaldevice design; receiving said geometric model of said anatomicalfeature(s); generating a finite element model representing both saidgeometric model of said anatomical feature(s) and said geometric modelof said candidate medical device design with a mesh generator; receivingmaterial properties of said anatomical feature(s) and said candidatemedical device design; receiving load data imposed on said candidatemedical device design and said anatomical feature(s); and simulating aninteraction between said anatomical feature(s) and said candidatemedical device design over at least one dynamic expansion andcontraction cycle of the anatomical feature(s) with astress/strain/deformation analyzer to determine predicted stresses,strains, and deformation of said candidate medical device design by saidload data.
 13. The method of claim 12 wherein the step of simulatingstresses, strains, and deformations is performed to a point of failureof said candidate medical device design.
 14. The method of claim 12wherein where said three-dimensional volumetric data are acquired via CTscan.
 15. The method of claim 12 wherein said three-dimensionalvolumetric data are acquired via MRI.
 16. The method of claim 12 whereinsaid geometric model for said anatomical feature(s) is generated by asoftware application which generates surface points from thethree-dimensional volumetric data, which are then converted intostereolithography, slice files, ICES files or a combination thereof. 17.The method of claim 12 wherein said step of generating a finite elementmodel is performed by using three-dimensional finite modeling software.18. The method of claim 12 wherein said stresses, strains, anddeformations are simulated by a non-linear finite element modelingsoftware application.
 19. The method of claim 17 wherein said threedimensional finite modeling software tessellates a geometric model intohexahedron brick elements and quadrilateral shell elements to create thefinite element model.
 20. The method of claim 18 wherein said non-linearfinite element modeling software application is configured toaccommodate a strain energy density of the form:W=a ₁₀(I ₁−3)+a ₀₁(I ₂−3)+a ₂₀(I ₁−3)² +a ₁₁(I ₁−3)(I ₂−3)+a ₀₂(I ₂−3)²+a ₃₀(I ₁−3)+a ₂₁(I ₁−3)²(I ₂−3)+a ₁₂(I ₁−3)(I ₂+3)² +a ₀₃(I ₂−3)³+½K(I₃−1)²with K=2(a ₁₀ +a ₀₁)/(1−2v) where a_(ij) are material parameters; v isPoisson's ratio; K is the bulk modulus given as a function of Poisson'sratio; and I₁, I₂, and I₃ are first, second, and third invariants of aright Cauchy-Green strain tensor, respectively.
 21. The method of claim12 wherein said stress/strain/deformation analysis is performed using anon-linear finite element analysis tool.
 22. The method of claim 12further comprising receiving results of said stress, strain, anddeformation analysis into a visualization tool and wherein saidvisualization tool visually presents one or more of said strains,stresses, and deformations of said medical device.
 23. The method ofclaim 22 wherein said visualization tool includes interactive softwarefor visualizing finite element analysis results on three-dimensionalgrids.